Overview

Brought to you by YData

Dataset statistics

Number of variables16
Number of observations1048532
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory917.8 MiB
Average record size in memory917.8 B

Variable types

Categorical5
Text9
DateTime1
Numeric1

Alerts

Application Number has unique values Unique

Reproduction

Analysis started2025-03-25 09:30:27.292128
Analysis finished2025-03-25 09:31:14.277527
Duration46.99 seconds
Software versionydata-profiling vv4.15.1
Download configurationconfig.json

Variables

Gender
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.9 MiB
Male
576225 
Female
461913 
Other
 
10394

Length

Max length6
Median length4
Mean length4.890979
Min length4

Characters and Unicode

Total characters5128348
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFemale
2nd rowFemale
3rd rowFemale
4th rowMale
5th rowFemale

Common Values

ValueCountFrequency (%)
Male 576225
55.0%
Female 461913
44.1%
Other 10394
 
1.0%

Length

2025-03-25T15:01:14.646067image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-25T15:01:14.857027image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
male 576225
55.0%
female 461913
44.1%
other 10394
 
1.0%

Most occurring characters

ValueCountFrequency (%)
e 1510445
29.5%
a 1038138
20.2%
l 1038138
20.2%
M 576225
 
11.2%
F 461913
 
9.0%
m 461913
 
9.0%
O 10394
 
0.2%
t 10394
 
0.2%
h 10394
 
0.2%
r 10394
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5128348
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1510445
29.5%
a 1038138
20.2%
l 1038138
20.2%
M 576225
 
11.2%
F 461913
 
9.0%
m 461913
 
9.0%
O 10394
 
0.2%
t 10394
 
0.2%
h 10394
 
0.2%
r 10394
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5128348
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1510445
29.5%
a 1038138
20.2%
l 1038138
20.2%
M 576225
 
11.2%
F 461913
 
9.0%
m 461913
 
9.0%
O 10394
 
0.2%
t 10394
 
0.2%
h 10394
 
0.2%
r 10394
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5128348
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1510445
29.5%
a 1038138
20.2%
l 1038138
20.2%
M 576225
 
11.2%
F 461913
 
9.0%
m 461913
 
9.0%
O 10394
 
0.2%
t 10394
 
0.2%
h 10394
 
0.2%
r 10394
 
0.2%

State/UT
Categorical

Distinct36
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.9 MiB
Gujarat
195439 
Maharashtra
109226 
Uttar Pradesh
99638 
Rajasthan
84900 
Karnataka
60585 
Other values (31)
498744 

Length

Max length40
Median length17
Mean length9.8940156
Min length3

Characters and Unicode

Total characters10374192
Distinct characters43
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUttar Pradesh
2nd rowMaharashtra
3rd rowRajasthan
4th rowTripura
5th rowGujarat

Common Values

ValueCountFrequency (%)
Gujarat 195439
18.6%
Maharashtra 109226
 
10.4%
Uttar Pradesh 99638
 
9.5%
Rajasthan 84900
 
8.1%
Karnataka 60585
 
5.8%
Telangana 59262
 
5.7%
Andhra Pradesh 55581
 
5.3%
Madhya Pradesh 40351
 
3.8%
Tamil Nadu 34976
 
3.3%
Haryana 20749
 
2.0%
Other values (26) 287825
27.5%

Length

2025-03-25T15:01:15.132314image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pradesh 211930
15.1%
gujarat 195439
13.9%
maharashtra 109226
 
7.8%
uttar 99638
 
7.1%
rajasthan 84900
 
6.0%
karnataka 60585
 
4.3%
telangana 59262
 
4.2%
andhra 55581
 
4.0%
and 41581
 
3.0%
madhya 40351
 
2.9%
Other values (37) 445967
31.8%

Most occurring characters

ValueCountFrequency (%)
a 2616677
25.2%
r 1047537
 
10.1%
h 823032
 
7.9%
t 723243
 
7.0%
n 507186
 
4.9%
s 501191
 
4.8%
d 499010
 
4.8%
e 361846
 
3.5%
355928
 
3.4%
u 319165
 
3.1%
Other values (33) 2619377
25.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10374192
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 2616677
25.2%
r 1047537
 
10.1%
h 823032
 
7.9%
t 723243
 
7.0%
n 507186
 
4.9%
s 501191
 
4.8%
d 499010
 
4.8%
e 361846
 
3.5%
355928
 
3.4%
u 319165
 
3.1%
Other values (33) 2619377
25.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10374192
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 2616677
25.2%
r 1047537
 
10.1%
h 823032
 
7.9%
t 723243
 
7.0%
n 507186
 
4.9%
s 501191
 
4.8%
d 499010
 
4.8%
e 361846
 
3.5%
355928
 
3.4%
u 319165
 
3.1%
Other values (33) 2619377
25.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10374192
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 2616677
25.2%
r 1047537
 
10.1%
h 823032
 
7.9%
t 723243
 
7.0%
n 507186
 
4.9%
s 501191
 
4.8%
d 499010
 
4.8%
e 361846
 
3.5%
355928
 
3.4%
u 319165
 
3.1%
Other values (33) 2619377
25.2%
Distinct733
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.5 MiB
2025-03-25T15:01:15.638726image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length26
Median length22
Mean length8.4668403
Min length3

Characters and Unicode

Total characters8877753
Distinct characters54
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBareilly
2nd rowParbhani
3rd rowDungarpur
4th rowKhowai
5th rowBanaskantha
ValueCountFrequency (%)
south 16843
 
1.4%
west 16578
 
1.4%
north 14944
 
1.2%
east 13747
 
1.1%
goa 10721
 
0.9%
sikkim 10507
 
0.9%
chandigarh 10247
 
0.8%
nagar 10216
 
0.8%
godavari 8589
 
0.7%
delhi 8474
 
0.7%
Other values (736) 1102773
90.1%
2025-03-25T15:01:16.136813image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1816522
20.5%
r 750819
 
8.5%
i 539018
 
6.1%
h 531618
 
6.0%
n 512836
 
5.8%
u 405314
 
4.6%
d 362555
 
4.1%
l 319329
 
3.6%
o 301210
 
3.4%
t 283374
 
3.2%
Other values (44) 3055158
34.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8877753
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1816522
20.5%
r 750819
 
8.5%
i 539018
 
6.1%
h 531618
 
6.0%
n 512836
 
5.8%
u 405314
 
4.6%
d 362555
 
4.1%
l 319329
 
3.6%
o 301210
 
3.4%
t 283374
 
3.2%
Other values (44) 3055158
34.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8877753
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1816522
20.5%
r 750819
 
8.5%
i 539018
 
6.1%
h 531618
 
6.0%
n 512836
 
5.8%
u 405314
 
4.6%
d 362555
 
4.1%
l 319329
 
3.6%
o 301210
 
3.4%
t 283374
 
3.2%
Other values (44) 3055158
34.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8877753
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1816522
20.5%
r 750819
 
8.5%
i 539018
 
6.1%
h 531618
 
6.0%
n 512836
 
5.8%
u 405314
 
4.6%
d 362555
 
4.1%
l 319329
 
3.6%
o 301210
 
3.4%
t 283374
 
3.2%
Other values (44) 3055158
34.4%
Distinct56
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size96.2 MiB
2025-03-25T15:01:16.345668image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length69
Median length58
Mean length47.245495
Min length10

Characters and Unicode

Total characters49538413
Distinct characters51
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDakshinanchal Vidyut Vitaran Nigam Limited (DVVNL), Agra Zone
2nd rowMaharashtra State Electricity Distribution Company Limited (MSEDCL)
3rd rowJodhpur Vidyut Vitran Nigam Limited (JdVVNL)
4th rowTripura State Electricity Corporation Limited (TSECL)
5th rowMadhya Gujarat Vij Company Limited (MGVCL), Vadodara
ValueCountFrequency (%)
limited 704833
 
11.1%
company 433237
 
6.8%
power 372910
 
5.9%
corporation 259362
 
4.1%
distribution 215545
 
3.4%
electricity 185106
 
2.9%
vidyut 168030
 
2.6%
gujarat 156430
 
2.5%
vij 156430
 
2.5%
of 149659
 
2.4%
Other values (125) 3561072
56.0%
2025-03-25T15:01:16.742130image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5314082
 
10.7%
i 4162082
 
8.4%
a 3981721
 
8.0%
t 3310175
 
6.7%
r 3048086
 
6.2%
o 2622056
 
5.3%
e 2306881
 
4.7%
n 2251360
 
4.5%
d 1724368
 
3.5%
m 1715714
 
3.5%
Other values (41) 19101888
38.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 49538413
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5314082
 
10.7%
i 4162082
 
8.4%
a 3981721
 
8.0%
t 3310175
 
6.7%
r 3048086
 
6.2%
o 2622056
 
5.3%
e 2306881
 
4.7%
n 2251360
 
4.5%
d 1724368
 
3.5%
m 1715714
 
3.5%
Other values (41) 19101888
38.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 49538413
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5314082
 
10.7%
i 4162082
 
8.4%
a 3981721
 
8.0%
t 3310175
 
6.7%
r 3048086
 
6.2%
o 2622056
 
5.3%
e 2306881
 
4.7%
n 2251360
 
4.5%
d 1724368
 
3.5%
m 1715714
 
3.5%
Other values (41) 19101888
38.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 49538413
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5314082
 
10.7%
i 4162082
 
8.4%
a 3981721
 
8.0%
t 3310175
 
6.7%
r 3048086
 
6.2%
o 2622056
 
5.3%
e 2306881
 
4.7%
n 2251360
 
4.5%
d 1724368
 
3.5%
m 1715714
 
3.5%
Other values (41) 19101888
38.6%
Distinct366
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size8.0 MiB
Minimum2024-01-01 00:00:00
Maximum2024-12-31 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-03-25T15:01:16.862303image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-25T15:01:16.987322image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.0 MiB
Rejected
736765 
Accepted
311767 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8388256
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAccepted
2nd rowRejected
3rd rowAccepted
4th rowRejected
5th rowRejected

Common Values

ValueCountFrequency (%)
Rejected 736765
70.3%
Accepted 311767
29.7%

Length

2025-03-25T15:01:17.145785image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-25T15:01:17.188477image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
rejected 736765
70.3%
accepted 311767
29.7%

Most occurring characters

ValueCountFrequency (%)
e 2833829
33.8%
c 1360299
16.2%
d 1048532
 
12.5%
t 1048532
 
12.5%
j 736765
 
8.8%
R 736765
 
8.8%
A 311767
 
3.7%
p 311767
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8388256
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 2833829
33.8%
c 1360299
16.2%
d 1048532
 
12.5%
t 1048532
 
12.5%
j 736765
 
8.8%
R 736765
 
8.8%
A 311767
 
3.7%
p 311767
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8388256
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 2833829
33.8%
c 1360299
16.2%
d 1048532
 
12.5%
t 1048532
 
12.5%
j 736765
 
8.8%
R 736765
 
8.8%
A 311767
 
3.7%
p 311767
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8388256
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 2833829
33.8%
c 1360299
16.2%
d 1048532
 
12.5%
t 1048532
 
12.5%
j 736765
 
8.8%
R 736765
 
8.8%
A 311767
 
3.7%
p 311767
 
3.7%
Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.0 MiB
3 - 4 KW
734088 
4 - 5 KW
154262 
5 - 6 KW
76993 
2 - 3 KW
 
58367
Above 6 KW
 
20863

Length

Max length10
Median length8
Mean length8.0397947
Min length8

Characters and Unicode

Total characters8429982
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3 - 4 KW
2nd row3 - 4 KW
3rd row3 - 4 KW
4th row5 - 6 KW
5th row3 - 4 KW

Common Values

ValueCountFrequency (%)
3 - 4 KW 734088
70.0%
4 - 5 KW 154262
 
14.7%
5 - 6 KW 76993
 
7.3%
2 - 3 KW 58367
 
5.6%
Above 6 KW 20863
 
2.0%
1 - 2 KW 3959
 
0.4%

Length

2025-03-25T15:01:17.282634image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-25T15:01:17.404835image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
kw 1048532
25.1%
1027669
24.6%
4 888350
21.3%
3 792455
19.0%
5 231255
 
5.5%
6 97856
 
2.3%
2 62326
 
1.5%
above 20863
 
0.5%
1 3959
 
0.1%

Most occurring characters

ValueCountFrequency (%)
3124733
37.1%
W 1048532
 
12.4%
K 1048532
 
12.4%
- 1027669
 
12.2%
4 888350
 
10.5%
3 792455
 
9.4%
5 231255
 
2.7%
6 97856
 
1.2%
2 62326
 
0.7%
A 20863
 
0.2%
Other values (5) 87411
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8429982
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3124733
37.1%
W 1048532
 
12.4%
K 1048532
 
12.4%
- 1027669
 
12.2%
4 888350
 
10.5%
3 792455
 
9.4%
5 231255
 
2.7%
6 97856
 
1.2%
2 62326
 
0.7%
A 20863
 
0.2%
Other values (5) 87411
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8429982
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3124733
37.1%
W 1048532
 
12.4%
K 1048532
 
12.4%
- 1027669
 
12.2%
4 888350
 
10.5%
3 792455
 
9.4%
5 231255
 
2.7%
6 97856
 
1.2%
2 62326
 
0.7%
A 20863
 
0.2%
Other values (5) 87411
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8429982
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3124733
37.1%
W 1048532
 
12.4%
K 1048532
 
12.4%
- 1027669
 
12.2%
4 888350
 
10.5%
3 792455
 
9.4%
5 231255
 
2.7%
6 97856
 
1.2%
2 62326
 
0.7%
A 20863
 
0.2%
Other values (5) 87411
 
1.0%

Application Number
Real number (ℝ)

Unique 

Distinct1048532
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54941231
Minimum10000006
Maximum99999933
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 MiB
2025-03-25T15:01:17.645927image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum10000006
5-th percentile14466901
Q132432651
median54913096
Q377445121
95-th percentile95495833
Maximum99999933
Range89999927
Interquartile range (IQR)45012470

Descriptive statistics

Standard deviation25985511
Coefficient of variation (CV)0.47296921
Kurtosis-1.199971
Mean54941231
Median Absolute Deviation (MAD)22506724
Skewness0.0024828797
Sum5.7607638 × 1013
Variance6.7524676 × 1014
MonotonicityNot monotonic
2025-03-25T15:01:17.782555image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13976094 1
 
< 0.1%
71333204 1
 
< 0.1%
96237088 1
 
< 0.1%
49598076 1
 
< 0.1%
93968261 1
 
< 0.1%
32520172 1
 
< 0.1%
67415221 1
 
< 0.1%
79732248 1
 
< 0.1%
58464843 1
 
< 0.1%
26789985 1
 
< 0.1%
Other values (1048522) 1048522
> 99.9%
ValueCountFrequency (%)
10000006 1
< 0.1%
10000241 1
< 0.1%
10000597 1
< 0.1%
10000685 1
< 0.1%
10000844 1
< 0.1%
10001167 1
< 0.1%
10001226 1
< 0.1%
10001271 1
< 0.1%
10001367 1
< 0.1%
10001398 1
< 0.1%
ValueCountFrequency (%)
99999933 1
< 0.1%
99999815 1
< 0.1%
99999796 1
< 0.1%
99999774 1
< 0.1%
99999736 1
< 0.1%
99999729 1
< 0.1%
99999719 1
< 0.1%
99999714 1
< 0.1%
99999603 1
< 0.1%
99999582 1
< 0.1%
Distinct379
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.6 MiB
2025-03-25T15:01:17.988352image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.5946733
Min length8

Characters and Unicode

Total characters9011790
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-11-15
2nd rowDeclined
3rd row2024-08-12
4th rowDeclined
5th rowDeclined
ValueCountFrequency (%)
declined 736765
70.3%
2024-07-23 1576
 
0.2%
2024-07-17 1567
 
0.1%
2024-07-29 1556
 
0.1%
2024-07-22 1550
 
0.1%
2024-07-25 1524
 
0.1%
2024-08-02 1520
 
0.1%
2024-08-03 1510
 
0.1%
2024-08-01 1508
 
0.1%
2024-07-20 1507
 
0.1%
Other values (369) 297949
28.4%
2025-03-25T15:01:18.283497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1473530
16.4%
2 801375
8.9%
D 736765
8.2%
c 736765
8.2%
i 736765
8.2%
l 736765
8.2%
n 736765
8.2%
d 736765
8.2%
0 679912
7.5%
- 623534
6.9%
Other values (8) 1012849
11.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9011790
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1473530
16.4%
2 801375
8.9%
D 736765
8.2%
c 736765
8.2%
i 736765
8.2%
l 736765
8.2%
n 736765
8.2%
d 736765
8.2%
0 679912
7.5%
- 623534
6.9%
Other values (8) 1012849
11.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9011790
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1473530
16.4%
2 801375
8.9%
D 736765
8.2%
c 736765
8.2%
i 736765
8.2%
l 736765
8.2%
n 736765
8.2%
d 736765
8.2%
0 679912
7.5%
- 623534
6.9%
Other values (8) 1012849
11.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9011790
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1473530
16.4%
2 801375
8.9%
D 736765
8.2%
c 736765
8.2%
i 736765
8.2%
l 736765
8.2%
n 736765
8.2%
d 736765
8.2%
0 679912
7.5%
- 623534
6.9%
Other values (8) 1012849
11.2%
Distinct20
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.1 MiB
InfiniteLight Solar
 
52750
PowerSun Technologies
 
52738
IlluminateSun Technologies
 
52618
SunVolt Power
 
52535
SolarEdge Systems
 
52533
Other values (15)
785358 

Length

Max length27
Median length23
Mean length19.148124
Min length13

Characters and Unicode

Total characters20077421
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBrightSun Power
2nd rowEcoPower Solar
3rd rowSunVolt Power
4th rowPowerSun Technologies
5th rowIlluminateSun Technologies

Common Values

ValueCountFrequency (%)
InfiniteLight Solar 52750
 
5.0%
PowerSun Technologies 52738
 
5.0%
IlluminateSun Technologies 52618
 
5.0%
SunVolt Power 52535
 
5.0%
SolarEdge Systems 52533
 
5.0%
GreenSpark Solar 52529
 
5.0%
SkyPower Solar 52525
 
5.0%
EcoPower Solar 52520
 
5.0%
SolarCrest Enterprises 52515
 
5.0%
BrightSun Power 52502
 
5.0%
Other values (10) 522767
49.9%

Length

2025-03-25T15:01:18.403763image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
solar 315024
 
13.7%
energy 208799
 
9.1%
systems 157212
 
6.8%
solutions 156657
 
6.8%
technologies 105356
 
4.6%
power 105037
 
4.6%
enterprises 104882
 
4.5%
infinitelight 52750
 
2.3%
powersun 52738
 
2.3%
illuminatesun 52618
 
2.3%
Other values (19) 995077
43.1%

Most occurring characters

ValueCountFrequency (%)
e 2096766
 
10.4%
r 1677815
 
8.4%
n 1676317
 
8.3%
o 1626069
 
8.1%
S 1467476
 
7.3%
1257618
 
6.3%
a 1152736
 
5.7%
l 1049195
 
5.2%
s 995688
 
5.0%
t 891345
 
4.4%
Other values (26) 6186396
30.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 20077421
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 2096766
 
10.4%
r 1677815
 
8.4%
n 1676317
 
8.3%
o 1626069
 
8.1%
S 1467476
 
7.3%
1257618
 
6.3%
a 1152736
 
5.7%
l 1049195
 
5.2%
s 995688
 
5.0%
t 891345
 
4.4%
Other values (26) 6186396
30.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 20077421
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 2096766
 
10.4%
r 1677815
 
8.4%
n 1676317
 
8.3%
o 1626069
 
8.1%
S 1467476
 
7.3%
1257618
 
6.3%
a 1152736
 
5.7%
l 1049195
 
5.2%
s 995688
 
5.0%
t 891345
 
4.4%
Other values (26) 6186396
30.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 20077421
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 2096766
 
10.4%
r 1677815
 
8.4%
n 1676317
 
8.3%
o 1626069
 
8.1%
S 1467476
 
7.3%
1257618
 
6.3%
a 1152736
 
5.7%
l 1049195
 
5.2%
s 995688
 
5.0%
t 891345
 
4.4%
Other values (26) 6186396
30.8%
Distinct360
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.5 MiB
2025-03-25T15:01:18.719793image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.5450525
Min length7

Characters and Unicode

Total characters8959761
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-11-26
2nd rowDeclined
3rd row2024-08-24
4th rowDeclined
5th rowDeclined
ValueCountFrequency (%)
declined 736765
70.3%
pending 17343
 
1.7%
2024-08-05 1588
 
0.2%
2024-07-27 1527
 
0.1%
2024-08-10 1526
 
0.1%
2024-08-02 1524
 
0.1%
2024-07-31 1510
 
0.1%
2024-08-07 1506
 
0.1%
2024-08-09 1499
 
0.1%
2024-08-04 1498
 
0.1%
Other values (350) 282246
 
26.9%
2025-03-25T15:01:19.185189image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1490873
16.6%
n 771451
8.6%
2 764445
8.5%
d 754108
8.4%
i 754108
8.4%
l 736765
8.2%
D 736765
8.2%
c 736765
8.2%
0 635327
7.1%
- 588848
 
6.6%
Other values (10) 990306
11.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8959761
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1490873
16.6%
n 771451
8.6%
2 764445
8.5%
d 754108
8.4%
i 754108
8.4%
l 736765
8.2%
D 736765
8.2%
c 736765
8.2%
0 635327
7.1%
- 588848
 
6.6%
Other values (10) 990306
11.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8959761
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1490873
16.6%
n 771451
8.6%
2 764445
8.5%
d 754108
8.4%
i 754108
8.4%
l 736765
8.2%
D 736765
8.2%
c 736765
8.2%
0 635327
7.1%
- 588848
 
6.6%
Other values (10) 990306
11.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8959761
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1490873
16.6%
n 771451
8.6%
2 764445
8.5%
d 754108
8.4%
i 754108
8.4%
l 736765
8.2%
D 736765
8.2%
c 736765
8.2%
0 635327
7.1%
- 588848
 
6.6%
Other values (10) 990306
11.1%
Distinct356
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.5 MiB
2025-03-25T15:01:19.606788image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.5327868
Min length7

Characters and Unicode

Total characters8946900
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-11-28
2nd rowDeclined
3rd row2024-08-27
4th rowDeclined
5th rowDeclined
ValueCountFrequency (%)
declined 736765
70.3%
pending 21630
 
2.1%
2024-08-14 1530
 
0.1%
2024-08-13 1529
 
0.1%
2024-08-04 1528
 
0.1%
2024-08-07 1524
 
0.1%
2024-08-12 1516
 
0.1%
2024-08-06 1511
 
0.1%
2024-08-08 1504
 
0.1%
2024-08-10 1502
 
0.1%
Other values (346) 277993
 
26.5%
2025-03-25T15:01:20.129087image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1495160
16.7%
n 780025
8.7%
i 758395
8.5%
d 758395
8.5%
2 753021
8.4%
l 736765
8.2%
D 736765
8.2%
c 736765
8.2%
0 626479
7.0%
- 580274
 
6.5%
Other values (10) 984856
11.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8946900
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1495160
16.7%
n 780025
8.7%
i 758395
8.5%
d 758395
8.5%
2 753021
8.4%
l 736765
8.2%
D 736765
8.2%
c 736765
8.2%
0 626479
7.0%
- 580274
 
6.5%
Other values (10) 984856
11.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8946900
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1495160
16.7%
n 780025
8.7%
i 758395
8.5%
d 758395
8.5%
2 753021
8.4%
l 736765
8.2%
D 736765
8.2%
c 736765
8.2%
0 626479
7.0%
- 580274
 
6.5%
Other values (10) 984856
11.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8946900
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1495160
16.7%
n 780025
8.7%
i 758395
8.5%
d 758395
8.5%
2 753021
8.4%
l 736765
8.2%
D 736765
8.2%
c 736765
8.2%
0 626479
7.0%
- 580274
 
6.5%
Other values (10) 984856
11.0%
Distinct342
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.4 MiB
2025-03-25T15:01:20.446616image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.4030683
Min length7

Characters and Unicode

Total characters8810886
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-12-09
2nd rowDeclined
3rd row2024-09-22
4th rowDeclined
5th rowDeclined
ValueCountFrequency (%)
declined 736765
70.3%
pending 66968
 
6.4%
2024-09-04 1468
 
0.1%
2024-09-05 1426
 
0.1%
2024-09-03 1403
 
0.1%
2024-09-01 1400
 
0.1%
2024-09-08 1394
 
0.1%
2024-09-07 1393
 
0.1%
2024-09-06 1391
 
0.1%
2024-08-29 1378
 
0.1%
Other values (332) 233546
 
22.3%
2025-03-25T15:01:20.876981image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1540498
17.5%
n 870701
9.9%
i 803733
9.1%
d 803733
9.1%
l 736765
8.4%
c 736765
8.4%
D 736765
8.4%
2 616654
7.0%
0 540443
 
6.1%
- 489598
 
5.6%
Other values (10) 935231
10.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8810886
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1540498
17.5%
n 870701
9.9%
i 803733
9.1%
d 803733
9.1%
l 736765
8.4%
c 736765
8.4%
D 736765
8.4%
2 616654
7.0%
0 540443
 
6.1%
- 489598
 
5.6%
Other values (10) 935231
10.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8810886
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1540498
17.5%
n 870701
9.9%
i 803733
9.1%
d 803733
9.1%
l 736765
8.4%
c 736765
8.4%
D 736765
8.4%
2 616654
7.0%
0 540443
 
6.1%
- 489598
 
5.6%
Other values (10) 935231
10.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8810886
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1540498
17.5%
n 870701
9.9%
i 803733
9.1%
d 803733
9.1%
l 736765
8.4%
c 736765
8.4%
D 736765
8.4%
2 616654
7.0%
0 540443
 
6.1%
- 489598
 
5.6%
Other values (10) 935231
10.6%
Distinct334
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.4 MiB
2025-03-25T15:01:21.163824image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.3885451
Min length7

Characters and Unicode

Total characters8795658
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2024-12-17
2nd rowDeclined
3rd row2024-10-05
4th rowDeclined
5th rowDeclined
ValueCountFrequency (%)
declined 736765
70.3%
pending 72044
 
6.9%
2024-09-11 1422
 
0.1%
2024-09-16 1418
 
0.1%
2024-09-08 1398
 
0.1%
2024-09-15 1378
 
0.1%
2024-09-23 1377
 
0.1%
2024-09-10 1374
 
0.1%
2024-09-19 1372
 
0.1%
2024-09-12 1365
 
0.1%
Other values (324) 228619
 
21.8%
2025-03-25T15:01:21.845415image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1545574
17.6%
n 880853
10.0%
i 808809
9.2%
d 808809
9.2%
l 736765
8.4%
c 736765
8.4%
D 736765
8.4%
2 606402
 
6.9%
0 524647
 
6.0%
- 479446
 
5.5%
Other values (10) 930823
10.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8795658
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1545574
17.6%
n 880853
10.0%
i 808809
9.2%
d 808809
9.2%
l 736765
8.4%
c 736765
8.4%
D 736765
8.4%
2 606402
 
6.9%
0 524647
 
6.0%
- 479446
 
5.5%
Other values (10) 930823
10.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8795658
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1545574
17.6%
n 880853
10.0%
i 808809
9.2%
d 808809
9.2%
l 736765
8.4%
c 736765
8.4%
D 736765
8.4%
2 606402
 
6.9%
0 524647
 
6.0%
- 479446
 
5.5%
Other values (10) 930823
10.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8795658
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1545574
17.6%
n 880853
10.0%
i 808809
9.2%
d 808809
9.2%
l 736765
8.4%
c 736765
8.4%
D 736765
8.4%
2 606402
 
6.9%
0 524647
 
6.0%
- 479446
 
5.5%
Other values (10) 930823
10.6%
Distinct329
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.4 MiB
2025-03-25T15:01:22.597491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.3773581
Min length7

Characters and Unicode

Total characters8783928
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2024-12-20
2nd rowDeclined
3rd row2024-10-12
4th rowDeclined
5th rowDeclined
ValueCountFrequency (%)
declined 736765
70.3%
pending 75954
 
7.2%
2024-09-18 1431
 
0.1%
2024-09-17 1426
 
0.1%
2024-09-21 1397
 
0.1%
2024-09-26 1385
 
0.1%
2024-09-22 1374
 
0.1%
2024-09-28 1374
 
0.1%
2024-09-24 1366
 
0.1%
2024-09-20 1366
 
0.1%
Other values (319) 224694
 
21.4%
2025-03-25T15:01:23.456898image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1549484
17.6%
n 888673
10.1%
i 812719
9.3%
d 812719
9.3%
l 736765
8.4%
c 736765
8.4%
D 736765
8.4%
2 597570
 
6.8%
0 513163
 
5.8%
- 471626
 
5.4%
Other values (10) 927679
10.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8783928
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1549484
17.6%
n 888673
10.1%
i 812719
9.3%
d 812719
9.3%
l 736765
8.4%
c 736765
8.4%
D 736765
8.4%
2 597570
 
6.8%
0 513163
 
5.8%
- 471626
 
5.4%
Other values (10) 927679
10.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8783928
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1549484
17.6%
n 888673
10.1%
i 812719
9.3%
d 812719
9.3%
l 736765
8.4%
c 736765
8.4%
D 736765
8.4%
2 597570
 
6.8%
0 513163
 
5.8%
- 471626
 
5.4%
Other values (10) 927679
10.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8783928
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1549484
17.6%
n 888673
10.1%
i 812719
9.3%
d 812719
9.3%
l 736765
8.4%
c 736765
8.4%
D 736765
8.4%
2 597570
 
6.8%
0 513163
 
5.8%
- 471626
 
5.4%
Other values (10) 927679
10.6%
Distinct316
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.3 MiB
2025-03-25T15:01:24.141629image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.2579483
Min length7

Characters and Unicode

Total characters8658723
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowPending
2nd rowDeclined
3rd row2024-12-05
4th rowDeclined
5th rowDeclined
ValueCountFrequency (%)
declined 736765
70.3%
pending 117689
 
11.2%
2024-10-27 1231
 
0.1%
2024-10-18 1214
 
0.1%
2024-10-30 1212
 
0.1%
2024-10-31 1191
 
0.1%
2024-10-26 1191
 
0.1%
2024-11-07 1191
 
0.1%
2024-10-21 1186
 
0.1%
2024-10-23 1172
 
0.1%
Other values (306) 184490
 
17.6%
2025-03-25T15:01:24.928144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1591219
18.4%
n 972143
11.2%
i 854454
9.9%
d 854454
9.9%
l 736765
8.5%
c 736765
8.5%
D 736765
8.5%
2 492415
 
5.7%
0 410830
 
4.7%
- 388156
 
4.5%
Other values (10) 884757
10.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8658723
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1591219
18.4%
n 972143
11.2%
i 854454
9.9%
d 854454
9.9%
l 736765
8.5%
c 736765
8.5%
D 736765
8.5%
2 492415
 
5.7%
0 410830
 
4.7%
- 388156
 
4.5%
Other values (10) 884757
10.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8658723
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1591219
18.4%
n 972143
11.2%
i 854454
9.9%
d 854454
9.9%
l 736765
8.5%
c 736765
8.5%
D 736765
8.5%
2 492415
 
5.7%
0 410830
 
4.7%
- 388156
 
4.5%
Other values (10) 884757
10.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8658723
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1591219
18.4%
n 972143
11.2%
i 854454
9.9%
d 854454
9.9%
l 736765
8.5%
c 736765
8.5%
D 736765
8.5%
2 492415
 
5.7%
0 410830
 
4.7%
- 388156
 
4.5%
Other values (10) 884757
10.2%

Interactions

2025-03-25T15:01:07.157365image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-03-25T15:01:25.029275image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Acceptance StatusApplication NumberGenderProduction Capacity (KW)State/UTVendor Organization
Acceptance Status1.0000.0000.0000.0000.1160.000
Application Number0.0001.0000.0000.0000.0000.000
Gender0.0000.0001.0000.0010.0010.000
Production Capacity (KW)0.0000.0000.0011.0000.0020.000
State/UT0.1160.0000.0010.0021.0000.000
Vendor Organization0.0000.0000.0000.0000.0001.000

Missing values

2025-03-25T15:01:08.066425image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-03-25T15:01:09.846618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

GenderState/UTDistrictDiscom NameRegistration DateAcceptance StatusProduction Capacity (KW)Application NumberApplication Approved DateVendor OrganizationVendor Selection DateVendor Acceptance DateInstallation DateInspection DateSubsidy Redeemed DateSubsidy Released Date
0FemaleUttar PradeshBareillyDakshinanchal Vidyut Vitaran Nigam Limited (DVVNL), Agra Zone2024-11-03Accepted3 - 4 KW713332042024-11-15BrightSun Power2024-11-262024-11-282024-12-092024-12-172024-12-20Pending
1FemaleMaharashtraParbhaniMaharashtra State Electricity Distribution Company Limited (MSEDCL)2024-10-02Rejected3 - 4 KW96237088DeclinedEcoPower SolarDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
2FemaleRajasthanDungarpurJodhpur Vidyut Vitran Nigam Limited (JdVVNL)2024-07-30Accepted3 - 4 KW495980762024-08-12SunVolt Power2024-08-242024-08-272024-09-222024-10-052024-10-122024-12-05
3MaleTripuraKhowaiTripura State Electricity Corporation Limited (TSECL)2024-12-29Rejected5 - 6 KW99541398DeclinedPowerSun TechnologiesDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
4FemaleGujaratBanaskanthaMadhya Gujarat Vij Company Limited (MGVCL), Vadodara2024-08-05Rejected3 - 4 KW17000352DeclinedIlluminateSun TechnologiesDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
5MaleGoaSouth GoaGoa Electricity Department2024-07-14Accepted4 - 5 KW806500722024-07-20SunBeam Energy Solutions2024-07-262024-07-282024-09-032024-09-142024-09-242024-11-16
6MaleTelanganaRajanna SircillaNorthern Power Distribution Company of Telangana Limited (TSNPDCL)2024-07-30Accepted4 - 5 KW108495502024-08-14SolarPeak Innovations2024-08-262024-08-302024-10-062024-10-192024-10-292024-11-14
7MaleTamil NaduRanipetTamil Nadu Generation and Distribution Corporation Limited (TANGEDCO)2024-07-22RejectedAbove 6 KW85659182DeclinedBrightSun PowerDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
8FemaleNagalandKohimaPowerGrid Corporation of India2024-11-17Accepted2 - 3 KW454039902024-11-27SunWave Energy2024-12-062024-12-08PendingPendingPendingPending
9FemaleGoaSouth GoaGoa Electricity Department2024-10-30Accepted2 - 3 KW238926392024-11-05SunVolt Power2024-11-122024-11-152024-12-212024-12-31PendingPending
GenderState/UTDistrictDiscom NameRegistration DateAcceptance StatusProduction Capacity (KW)Application NumberApplication Approved DateVendor OrganizationVendor Selection DateVendor Acceptance DateInstallation DateInspection DateSubsidy Redeemed DateSubsidy Released Date
1048522OtherKarnatakaBagalkotKarnataka Power Corporation Limited (KPCL)2024-03-25Rejected3 - 4 KW12660616DeclinedBrightSun PowerDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048523FemaleUttar PradeshKanpur DehatPashchimanchal Vidyut Vitran Nigam Limited (PVVNL), Meerut Zone2024-04-15Accepted3 - 4 KW376136482024-04-21IlluminateSun Technologies2024-04-272024-05-012024-05-252024-06-012024-06-082024-07-22
1048524FemaleBiharNawadaNorth Bihar Power Distribution Company Limited (NBPDCL)2024-08-01Accepted3 - 4 KW360197872024-08-13SunRise Renewable Solutions2024-08-202024-08-252024-09-052024-09-122024-09-152024-11-13
1048525FemaleJharkhandGiridihPowerGrid Corporation of India2024-11-19Rejected3 - 4 KW77365520DeclinedGreenRay Solar SystemsDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048526MaleMaharashtraDhuleAdani Electricity Mumbai Limited2024-05-30Rejected3 - 4 KW44742575DeclinedEcoSolar EnterprisesDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048527MaleGujaratTapiUttar Gujarat Vij Company Limited (UGVCL), Mehsana2024-08-04Accepted3 - 4 KW169790222024-08-15SunWave Energy2024-08-302024-09-012024-09-212024-10-012024-10-112024-11-26
1048528MaleKarnatakaChikkaballapurBangalore Electricity Supply Company Limited (BESCOM)2024-08-16Accepted3 - 4 KW343652282024-08-31IlluminateSun Technologies2024-09-152024-09-212024-10-122024-10-242024-10-312024-11-10
1048529FemaleHimachal PradeshHamirpurPowerGrid Corporation of India2024-03-14Accepted3 - 4 KW137727802024-03-21BrightSun Power2024-03-282024-04-032024-04-232024-05-082024-05-172024-05-25
1048530MaleGujaratGir SomnathPaschim Gujarat Vij Company Limited (PGVCL), Rajkot2024-09-09Rejected3 - 4 KW82001920DeclinedSolarEdge SystemsDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048531FemaleTamil NaduKanchipuramTamil Nadu Generation and Distribution Corporation Limited (TANGEDCO)2024-10-13Rejected3 - 4 KW13976094DeclinedGreenSpark SolarDeclinedDeclinedDeclinedDeclinedDeclinedDeclined